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Nonparametric locally efficient estimation of the Treatment Specific Survival distribution with right Censored Data and Covariates in Observational Studies

2000; Institute of Electrical and Electronics Engineers; Linguagem: Inglês

10.1007/978-1-4612-1284-3_3

2198-3224

Alan Hubbard, Mark J. van der Laan, James M. Robins,

Statistical Methods and Bayesian Inference

In many observational studies one is concerned with comparing treatment specific survival distributions in the presence of confounding factors and censoring. In this paper we develop locally efficient point and interval estimators of these survival distributions which adjust for confounding by using an estimate of the propensity score and concurrently allow for dependent censoring. The proposed methodology is an application of a general methodology for construction of locally efficient estimators as presented in Robins (1993) and Robins and Rotnitzky (1992). The practical performance of the methods are tested with a simulation study.